@misc{13999, abstract = {{A very promising approach for the ultrasonic identification of highly damping viscoelastic polymers has been proposed by Rautenberg. He uses transmission measurements through hollow cylindrical shaped test samples which are modeled as waveguides. The measurement effect relies on multiple mode-conversions at the waveguide's outer and inner boundaries and is evaluated based on an inverse approach. In this contribution we discuss different signal characteristics of the obtained dispersed signals with respect to their sensitivity to certain material parameters. Based on these sensitivities we propose a multiphase optimization scheme to increase the optimization's convergence.}}, author = {{Bause, Fabian and Rautenberg, Jens and Henning, Bernd}}, title = {{{Sensitivity study of signal characteristics for an inverse waveguide based approach of material characterization}}}, year = {{2012}}, } @inproceedings{30531, author = {{Hu, Manli and Fröhleke, Norbert and Peters, Wilhelm and Böcker, Joachim}}, booktitle = {{IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society}}, publisher = {{IEEE}}, title = {{{Multi-objective optimization of LCC resonant converter applied in VLF HV generator}}}, doi = {{10.1109/iecon.2011.6119522}}, year = {{2012}}, } @inproceedings{22164, abstract = {{Generative production techniques have the advantage of manufacturing parts via an additive process without needing a forming tool. One of these additive manufacturing technologies is "Fused Deposition Modeling" (FDM). It is one of the most used additive manufacturing processes to produce prototypes and end-use parts. From a 3D-CAD data set, components and assemblies are manufactured out of thermoplastic material layer by layer by means of an additive process. An extrusion head deposits the molten thermoplastic filament to create each layer with a particular tool path. Due to the thermal fusion the material bonds with the layer beneath and solidifies. Thus a permanent bonding of two layers is formed. In this paper the mechanical data of parts, manufactured with the system Fortus 400mc from Stratasys with the material Ultem*9085 are presented. Tensile and flexural tests according to both, the ASTM and the ISO standard, are conducted. Test specimens are generated with the standard parameters of the native software in different build directions. The tests show different strength and strain characteristics that depend on the given structure as a result of the build direction. Furthermore tensile specimens according to the ASTM standard are generated with changed parameters of the native software to increase the mechanical strength properties. The results are compared to injection molded strength properties.}}, author = {{Bagsik, A. and Schöppner, Volker and Klemp, E.}}, booktitle = {{1st International Conference on Thermo-Mechanically Graded Materials}}, isbn = {{9783942267588}}, pages = {{129--134}}, title = {{{Tensile and Flexural Properties of Fused Deposition Modeling Parts Manufactured with ULTEM*9085}}}, volume = {{1}}, year = {{2012}}, } @inproceedings{22024, abstract = {{Generative production techniques have the advantage of manufacturing parts via an additive process without needing a forming tool. One of these additive manufacturing technologies is “Fused Deposition Modeling” (FDM). It is one of the most used additive manufacturing processes to produce prototypes and end-use parts. From a 3D-CAD data set, components and assemblies are manufactured out of thermoplastic material layer by layer by means of an additive process. An extrusion head deposits the molten thermoplastic filament to create each layer with a particular tool path. In this paper the mechanical data of parts, manufactured with the system Fortus 400mc from Stratasys with the material Ultem*9085 are presented. Tensile specimens are generated with the standard parameters as well as with changed parameters of the native software to analyze the influence of these parameters on the mechanical strength properties. The tensile tests show different strength and strain characteristics that depend on the given structure and as a result of the build direction. Furthermore the toolpath parameters have an effect on the strength characteristics and the break behavior. In addition, tensile specimens are tested under the influence of different temperatures and after a thermal cycling. }}, author = {{Bagsik, A. and Schöppner, Volker and Klemp, E.}}, booktitle = {{5th International Conference on Polymer and Mould Innovations}}, pages = {{266--272}}, publisher = {{Centre for Polymer and Material Technology, Univ. College, Ghent Univ.}}, title = {{{Extensive Analysis of the mechanical strength properties of Fused Deposition Modeling Parts manufactured with ULTEM 9085}}}, doi = {{https://www.tib.eu/de/suchen/id/TIBKAT%3A756276616}}, volume = {{5}}, year = {{2012}}, } @article{29409, author = {{Ringkamp, M. and Ober-Blöbaum, Sina and Dellnitz, M. and Schütze, O.}}, journal = {{Engineering Optimization}}, pages = {{1117--1146}}, title = {{{Handling high dimensional problems with multi-objective continuation methods via successive approximation of the tangent space}}}, volume = {{44(6)}}, year = {{2012}}, } @inproceedings{29451, author = {{Flaßkamp, K. and Murphey, T. and Ober-Blöbaum, Sina}}, booktitle = {{51st IEEE International Conference on Decision and Control}}, location = {{Maui, USA}}, pages = {{707--712}}, title = {{{Switching time optimization in discretized hybrid dynamical systems}}}, year = {{2012}}, } @inproceedings{29533, author = {{Pook, Sebastian and Gausemeier, J{\"u}rgen and Dorociak, Rafal}}, booktitle = {{The Annual Reliability and Maintainability Symposium – RAMS 2012}}, title = {{{Securing the reliability of tomorrow's systems with Self-Optimization}}}, year = {{2012}}, } @inproceedings{28646, author = {{Pook, Sebastian and Gausemeier, J{\"u}rgen and Dorociak, Rafal}}, title = {{{Securing the reliability of tomorrow's systems with Self-Optimization}}}, year = {{2012}}, } @inproceedings{25810, abstract = {{The analysis of production systems by the use of discrete, event-based simulation is widely used and accepted as decision support method. It aims either at the comparison of competitive designs or the identification of a “best possible” configuration of the simulation model. Here, combinatorial techniques of simulation and optimization methods support the user in finding optimal solutions, which typically result in long computation times and though often prohibit a practical application in today’s industry. This paper presents a fast converging procedure as a combination of a swarm heuristic, namely the particle swarm optimization, and the material flow simulation to close this gap. Faster convergence is realized by a specific extension of classic PSO implementations. First results show the applicability with a simulation reference model. }}, author = {{Laroque, Christoph and Pater, Jan-Patrick}}, isbn = {{978-1-61208-234-9}}, pages = {{50--57}}, title = {{{An Automatic Approach for Parameter Optimization of Material Flow Simulation Models based on Particle Swarm Optimization}}}, year = {{2012}}, } @inproceedings{25811, author = {{Lauck, Sebastian and Hartmann, Philip and Laroque, Christoph}}, pages = {{20--25}}, publisher = {{International Institute of Informatics and Systemics}}, title = {{{Multi-Layer Architecture for Transition of Business-Models to common Software-Tools and Optimization of the Model-Structure exemplified with Microsoft SharePoint 2010}}}, year = {{2012}}, } @inproceedings{25818, author = {{Fischer, Jan-Hendrik and Delius, Robin and Horstkemper, Dennis and Laroque, Christoph}}, title = {{{Comparing a hybrid simulation & optimization approach with a purely stochastic optimization to increase the robustness of production plans}}}, year = {{2012}}, } @article{25821, author = {{Laroque, Christoph and Delius, Robin and Fischer, Jan-Hendrik}}, journal = {{International Journal on Advances in Systems and measurements}}, title = {{{Increase of robustness in production plans using a hybrid optimization and simulation approach}}}, year = {{2012}}, } @article{25820, author = {{Kaganova, Ekaterina}}, journal = {{Applied Mathematical Optimization and Modelling}}, title = {{{Robust solution approach to an uncertain CLSP problem}}}, year = {{2012}}, } @article{25827, abstract = {{Persistent trends like quickly changing production programs, increasing customer individual manufacturing and Sustainable Manufacturing create complex systems of objectives in manufacturing control. Service-oriented manufacturing systems and self-optimizing manufacturing resources offer the required flexibility to consider these objectives in accordance with the current organizational and economical situation. On the downside, this increase in flexibility make the control of manufacturing systems more difficult and presents new challenges regarding the scheduling. To meet these challenges, we developed scheduling framework that supports alternative process plans and considers the internal states trajectories of resources. In order to support the user in a complex decision-making environment, evolutionary multi-objective optimization is used to generate a set of relevant schedules and an interface to select the most appropriate schedule is provided. }}, author = {{Kl{\, Benjamin and Pater, Jan-Patrick and Honiden, Shinichi and Dangelmaier, Wilhelm}}, journal = {{Evolving Systems}}, number = {{1}}, pages = {{31--44}}, title = {{{A multi-objective evolutionary approach to scheduling for evolving manufacturing systems}}}, volume = {{3}}, year = {{2012}}, } @inproceedings{11833, abstract = {{In this paper we propose an approach to retrieve the geometry of an acoustic sensor network consisting of spatially distributed microphone arrays from unconstrained speech input. The calibration relies on Direction of Arrival (DoA) measurements which do not require a clock synchronization among the sensor nodes. The calibration problem is formulated as a cost function optimization task, which minimizes the squared differences between measured and predicted observations and additionally avoids the existence of minima that correspond to mirrored versions of the actual sensor orientations. Further, outlier measurements caused by reverberation are mitigated by a Random Sample Consensus (RANSAC) approach. The experimental results show a mean positioning error of at most 25 cm even in highly reverberant environments.}}, author = {{Jacob, Florian and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}}, booktitle = {{International Workshop on Acoustic Signal Enhancement (IWAENC 2012)}}, keywords = {{Unsupervised, geometry calibration, microphone arrays, position self-calibration}}, title = {{{Microphone Array Position Self-Calibration from Reverberant Speech Input}}}, year = {{2012}}, } @inproceedings{46397, abstract = {{In multiobjective optimization, set-based performance indicators are commonly used to assess the quality of a Pareto front approximation. Based on the scalarization obtained by these indicators, a performance comparison of multiobjective optimization algorithms becomes possible. The R2 and the Hypervolume (HV) indicator represent two recommended approaches which have shown a correlated behavior in recent empirical studies. Whereas the HV indicator has been comprehensively analyzed in the last years, almost no studies on the R2 indicator exist. In this paper, we thus perform a comprehensive investigation of the properties of the R2 indicator in a theoretical and empirical way. The influence of the number and distribution of the weight vectors on the optimal distribution of μ solutions is analyzed. Based on a comparative analysis, specific characteristics and differences of the R2 and HV indicator are presented.}}, author = {{Brockhoff, Dimo and Wagner, Tobias and Trautmann, Heike}}, booktitle = {{Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation}}, isbn = {{9781450311779}}, keywords = {{hypervolume indicator, multiobjective optimization, performance assessment, r2 indicator}}, pages = {{465–472}}, publisher = {{Association for Computing Machinery}}, title = {{{On the Properties of the R2 Indicator}}}, doi = {{10.1145/2330163.2330230}}, year = {{2012}}, } @inproceedings{46396, abstract = {{The steady supply of new optimization methods makes the algorithm selection problem (ASP) an increasingly pressing and challenging task, specially for real-world black-box optimization problems. The introduced approach considers the ASP as a cost-sensitive classification task which is based on Exploratory Landscape Analysis. Low-level features gathered by systematic sampling of the function on the feasible set are used to predict a well-performing algorithm out of a given portfolio. Example-specific label costs are defined by the expected runtime of each candidate algorithm. We use one-sided support vector regression to solve this learning problem. The approach is illustrated by means of the optimization problems and algorithms of the BBOB’09/10 workshop.}}, author = {{Bischl, Bernd and Mersmann, Olaf and Trautmann, Heike and Preuß, Mike}}, booktitle = {{Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation}}, isbn = {{9781450311779}}, keywords = {{machine learning, exploratory landscape analysis, fitness landscape, benchmarking, evolutionary optimization, bbob test set, algorithm selection}}, pages = {{313–320}}, publisher = {{Association for Computing Machinery}}, title = {{{Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning}}}, doi = {{10.1145/2330163.2330209}}, year = {{2012}}, } @article{46399, abstract = {{Meta-modeling has become a crucial tool in solving expensive optimization problems. Much of the work in the past has focused on finding a good regression method to model the fitness function. Examples include classical linear regression, splines, neural networks, Kriging and support vector regression. This paper specifically draws attention to the fact that assessing model accuracy is a crucial aspect in the meta-modeling framework. Resampling strategies such as cross-validation, subsampling, bootstrapping, and nested resampling are prominent methods for model validation and are systematically discussed with respect to possible pitfalls, shortcomings, and specific features. A survey of meta-modeling techniques within evolutionary optimization is provided. In addition, practical examples illustrating some of the pitfalls associated with model selection and performance assessment are presented. Finally, recommendations are given for choosing a model validation technique for a particular setting.}}, author = {{Bischl, B and Mersmann, O and Trautmann, Heike and Weihs, C}}, journal = {{Evolutionary Computation Journal}}, number = {{2}}, pages = {{249–275}}, title = {{{Resampling Methods in Model Validation}}}, doi = {{10.1162/EVCO_a_00069}}, volume = {{20}}, year = {{2012}}, } @inproceedings{48890, abstract = {{With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesman problem TSP. Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.}}, author = {{Mersmann, Olaf and Bischl, Bernd and Bossek, Jakob and Trautmann, Heike and Wagner, Markus and Neumann, Frank}}, booktitle = {{Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219}}, isbn = {{978-3-642-34412-1}}, keywords = {{2-opt, Classification, Feature Selection, MARS, TSP}}, pages = {{115–129}}, publisher = {{Springer-Verlag}}, title = {{{Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness}}}, year = {{2012}}, } @inbook{48888, abstract = {{With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesman problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.}}, author = {{Mersmann, Olaf and Bischl, Bernd and Bossek, Jakob and Trautmann, Heike and Wagner, Markus and Neumann, Frank}}, booktitle = {{Learning and Intelligent Optimization}}, isbn = {{978-3-642-34412-1 978-3-642-34413-8}}, pages = {{115–129}}, publisher = {{Springer Berlin Heidelberg}}, title = {{{Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness}}}, doi = {{10.1007/978-3-642-34413-8_9}}, volume = {{7219}}, year = {{2012}}, }